Networking Postdoctoral Fellow

Berkeley, Ca

Full Time Mid-level / Intermediate
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Networking Postdoctoral Fellow - 93965

Department:  CR-Computational Research

 

 

Lawrence Berkeley National Lab’s (LBNL)  Computational Research Division has an opening for a Networking Postdoctoral Fellow to join the team.

 

In this exciting role, you will work in an emerging new area on novel 5G and wireless research, combining optical networking and machine learning techniques. This work is to develop automation tools and optimization techniques that enable wired/wireless networks for distributed science experiments. These networks need to handle a large amount of application data across complex multi-domain infrastructure such as DOE facilities. Our automation and optimization techniques will be immensely useful in next-generation scientific discoveries that require massive amounts of data from a variety of sources including  exascale computing.

 

Leveraging techniques from network controllers, wireless and 5G, deep learning, as well as novel hardware accelerators e.g. FPGAs, this project explores how data is connected via sensors, processed quickly to predict user behavior and detect anomalies, and finally moved to scientists for discovery. The postdoc will work as part of a unique and engaging team developing techniques linking two major research themes namely network architecture and distributed edge ML methods. This work will lead to impactful results advancing state-of-the-art network research by building networks that automate connections and have the ability to understand application-network interaction to programmatically optimize their own behavior.

 

What You Will Do:

•  Design and develop networking concepts for real-time deployments.

•  Research 5G/wireless concepts.

•  Research distributed machine learning approaches that are applicable to edge networking environments.

•  Develop software libraries to process large network data sets that are publicly and privately available.

•  Explore techniques to port ML to FPGA and other accelerators.

•  Publish research findings in conferences and journals.

 

 

Additional Responsibilities as needed:

•  Collaborate with the Scientific Networking Division in ESnet at the lab at the testbed.

•  Collaboration with other teams in DOE facilities and related units.

•  Communicate research results to the wider networking community including industry.

•  Very strong analytical background in networking research algorithms, e.g., experience with designing controllers.

•  Prior experience deploying ML on FPGA boards or Raspberry pis.

 

 

What is required::

•  Ph.D. in related fields (Computer Science, Any Engineering Discipline such as Electronic and Controls, Mathematics).

•  Very strong analytical background in networking research algorithms, e.g., experience with designing controllers.

•  Strong analytical background in machine learning algorithms, e.g., experience with deep learning analysis and programming libraries.

•  Prior experience or demonstrated desire (e.g., papers) in networking and optimizing engineering problems.

•  Extremely high aptitude and desire for programming and building software infrastructure; object-oriented programming, machine learning libraries. The preferred language of experience is Python, but flexible to be extended to Matlab or other machine learning coding experiences.

•  Demonstrated ability (e.g., Github profile) to contribute to a large software framework.

•  Excellent communication skills that facilitate interdisciplinary work with multiple collaborators.

•  Strong publication history.

•  Demonstrated history working with machine learning libraries such as TensorFlow, Keras, or Scikit-learn.

 

 

Additional Desired Qualifications:

•  Prior experience in network automation tools like Ansible, Puppet.

•  Prior experience in working with large data sets and cloud infrastructures is desirable.

•  Willingness to learn techniques from multiple fields like ML, hardware, and networks are desirable.

 

Notes:

•  This is a full-time 2-year postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.

•  This position is represented by a union for collective bargaining purposes.

•  Salary will be predetermined based on postdoctoral step rates.

•  This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

•  This position will be remote initially, but limited to individuals residing in the United States tentatively until 2021 due to COVID-19. Once the Bay Area shelter-in-place restrictions are lifted, work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

 

 

How To Apply

Apply directly online at http://50.73.55.13/counter.php?id=210070 and follow the on-line instructions to complete the application process.

 

Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA) and strives to continue building community with these shared values and commitments.

 

Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab’s mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

 

Know your rights, click here for the supplement: "Equal Employment Opportunity is the Law" and the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.

Job region(s): North America
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